Attitude estimation of space target based on ISAR contour projection plane alignment

doi:10.23919/JSEE.2026.000055

Abstract

Abstract:

This paper proposes a space target attitude estimation method with inverse synthetic aperture radar (ISAR) images to address the challenges of difficult feature extraction, low estimation accuracy, and inefficiency in the attitude estimation of space targets. This method relies on ISAR contour projection plane alignment. Unlike traditional contour matching methods, this approach introduces an image plane alignment algorithm for different radar lines of sight (LOS). The algorithm aligns image planes from various frames, defined by their corresponding LOS and rotation axis, with those of a reference template library. This alignment resolves attitude mismatches during template matching caused by differences in image planes. The attitude estimation method first uses the Hausdorff distance as the contour matching criterion to enhance matching speed. Second, the contour projection plane alignment algorithm outputs the actual attitude for each frame. Third, the multi-solution attitude problem is addressed by combining the actual attitudes of each frame using the minimum distance method. Finally, an optimization algorithm is employed to improve estimation accuracy. This method demonstrates higher accuracy and efficiency compared to traditional approaches in scatter point imaging and electromagnetic simulation experiments.

Key words: inverse synthetic aperture radar (ISAR), attitude estimation, space target, contour matching, image plane alignment

Dan LIU, Yuzhe FAN, Lin’gang FAN, Chengzeng CHEN, Yan DAI. Attitude estimation of space target based on ISAR contour projection plane alignment[J]. Journal of Systems Engineering and Electronics, 2026, 37(2): 467-484.

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Frame sequence	Match attitude 1	Match attitude 2	Match attitude 3	Match attitude 4	Match attitude 5	Error
1st frame	(−73.1,64.3,−62.3)	(−26.2,−20.0,−125.6)	(26.2,20.0,54.4)	(73.1,−64.3,117.7)	(−16.2,−20.0,−125.6)	6.6
2nd frame	(62.2,−1.2,87.4)	(73.4,−56.8,112.0)	(−73.4,56.8,−68.0)	(−62.2.1.2,−92.6)	(49.6,−5.0,92.6)	7.9
3rd frame	(98.3,−4.4,104.0)	(71.4,−63.2,110.1)	(−86.0,53.6,−75.3)	(−88.5,14.3,−77.5)	(−81.4,63.2,−69.9)	12.1
4th frame	(125.3,−7.2,120.4)	(80.5,−57.5,107.3)	(113.4,−5.5,125.1)	(85.7,−60.9,114.4)	(115.3,−7.2,120,4)	5.4
5th frame	(155.0,11.0,148.0)	(85.5,−65.4,103.9)	(145.0,11.0,148.0)	(95.5,−65.4,103.9)	(147.8,−1.2,146.6)	7.9

Method	Error in attitude 1/($ ^\circ $)	Error in attitude 2/($ ^\circ $)	Error in attitude 3/($ ^\circ $)	Average time/s
Method in this paper	1.4	1.6	2.1	130
Shape context matching method	4.1	3.2	4.7	292
Projection energy method	2.9	3.3	6.1	205

Frame sequence	Match attitude 1	Match attitude 2	Match attitude 3	Match attitude 4	Match attitude 5	Error
1st frame	(26.2,20.0,54.4)	(73.1,−64.3,117.7)	(−72.6,56.1,−67.4)	(−33.6,−15.7,−117.7)	(82.6,−56.1,112.6)	3.6
2nd frame	(52.2,−1.2,87.4)	(54.5,1.9,81.8)	(−73.4,56.8,−68.0)	(84.7,−62.9,107.8)	(−62.2,1.2,−92.6)	4.4
3rd frame	(88.2,−24.6,102.7)	(87.1,−15.0,106.0)	(88.5,−14.3,102.5)	(88.3,−4.4,104.0)	(86.0,−53.6,104.7)	6.8
4th frame	(55.7,−60.9,114.4)	(−133.5,5.5,−54.9)	(135.3,−7.2,120.4)	(70.5,−57.5,107.3)	(−58.6,63.2,−56.1)	14.7
5th frame	(147.5,7.3,141.2)	(92.2,−57.8,103.6)	(155.0,11.0,148.0)	(85.5,−65.4,103.9)	(−92.2,57.8,−76.4)	7.9

Methods	Error in attitude 1/($ ^\circ $)	Error in attitude 2/($ ^\circ $)	Error in attitude 3/($ ^\circ $)	Average time/s
Method in this paper	2.1	2.5	2.4	125
Shape context matching method	4.6	5.8	4.9	285
Projection energy method	4.9	4.6	6.7	223
Line feature method	2.2	2.2	2.3	19

Methods	Error in attitude 1/($ ^\circ $)	Error in attitude 2/($ ^\circ $)	Error in attitude 3/($ ^\circ $)	Average time/s
Method in this paper	2.6	2.5	3.2	128
Line feature method	16.2	22.9	18.5	21